Depth estimation from 2D images is a classical computer vision problem that has been mostly tackled with methods from multiple view geometry [1]}, [2]}. Conventional stereo, structure-from-motion and SLAM approaches are already well-established and integrated to many practical applications. However, they rely on feature detection and matching that can be challenging especially when the scene lacks distinct details, and as a result the 3D reconstruction often becomes sparse and incomplete.
